منابع مشابه
Model identification in interactive influence diagrams using mutual information
Interactive influence diagrams (I-IDs) offer a transparent and intuitive representation for the decision-making problem in multiagent settings. They ascribe procedural models such as influence diagrams and I-IDs to model the behavior of other agents. Procedural models offer the benefit of understanding how others arrive at their behaviors. Accurate behavioral models of others facilitate optimal...
متن کاملInvestigating the mutual relationship between happiness and productivity using logit and probit regression (Case Study: LTU)
The Economics of Happiness is one of the relatively new areas in economics, which in recent years has found a significant place in the policy equation in most countries in the world. Today, it has been proven that there is a direct relationship between employee happiness and productivity of organizations, and this has led organizations to take steps to achieve greater productivity, the happines...
متن کاملIs mutual information adequate for feature selection in regression?
Feature selection is an important preprocessing step for many high-dimensional regression problems. One of the most common strategies is to select a relevant feature subset based on the mutual information criterion. However, no connection has been established yet between the use of mutual information and a regression error criterion in the machine learning literature. This is obviously an impor...
متن کاملBayesian Kernel and Mutual $k$-Nearest Neighbor Regression
We propose Bayesian extensions of two nonparametric regression methods which are kernel and mutual k-nearest neighbor regression methods. Derived based on Gaussian process models for regression, the extensions provide distributions for target value estimates and the framework to select the hyperparameters. It is shown that both the proposed methods asymptotically converge to kernel and mutual k...
متن کاملFeature Selection in Regression Tasks Using Conditional Mutual Information
This paper presents a supervised feature selection method applied to regression problems. The selection method uses a Dissimilarity matrix originally developed for classification problems, whose applicability is extended here to regression and built using the conditional mutual information between features with respect to a continuous relevant variable that represents the regression function. A...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Statistica Sinica
سال: 2024
ISSN: ['1017-0405', '1996-8507']
DOI: https://doi.org/10.5705/ss.202022.0035